First, we perform an extended quantitative analysis on the HICO-DET test set to validate the effectiveness of MSTR in a multi-scale environment.
MSTR uses multi-scale feature maps to explore the semantics of HOI existing in different scales.
In this section, we provide extensive quantitative results that shows the effectiveness of MSTR in capturing the interactions between humans and objects not only at different scales, but in various distances also (, adjacent interaction such as `holding a book' or remote interaction such as `throwing a frisbee').
To this end, we show quantitative results for multi-scale interactions according to 1) relative area of the human and the object, 2) the size of humans/objects, 3) distance between the human and object.
For each criterion, we measure the performance across three bins where each bin has an equal and sufficient amount of HOI ground-truth labels to cover (\(\sim \) 11,000 HOIs).
For comparison, we set QPIC [1]}, the state-of-the-art transformer-based approach that uses a single-scale feature map, as our baseline.
Note that in this appendix, the size, area, and distance are all calculated in normalized image coordinates.
